Computational Medicinal Chemistry to Target GPCRs

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Standard

Computational Medicinal Chemistry to Target GPCRs. / Kiss, Dóra Judit; Pándy-Szekeres, Gáspár; Keserű, György Miklós.

Comprehensive Pharmacology. Vol. 2 Elsevier, 2022. p. 84-114.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Kiss, DJ, Pándy-Szekeres, G & Keserű, GM 2022, Computational Medicinal Chemistry to Target GPCRs. in Comprehensive Pharmacology. vol. 2, Elsevier, pp. 84-114. https://doi.org/10.1016/B978-0-12-820472-6.00208-5

APA

Kiss, D. J., Pándy-Szekeres, G., & Keserű, G. M. (2022). Computational Medicinal Chemistry to Target GPCRs. In Comprehensive Pharmacology (Vol. 2, pp. 84-114). Elsevier. https://doi.org/10.1016/B978-0-12-820472-6.00208-5

Vancouver

Kiss DJ, Pándy-Szekeres G, Keserű GM. Computational Medicinal Chemistry to Target GPCRs. In Comprehensive Pharmacology. Vol. 2. Elsevier. 2022. p. 84-114 https://doi.org/10.1016/B978-0-12-820472-6.00208-5

Author

Kiss, Dóra Judit ; Pándy-Szekeres, Gáspár ; Keserű, György Miklós. / Computational Medicinal Chemistry to Target GPCRs. Comprehensive Pharmacology. Vol. 2 Elsevier, 2022. pp. 84-114

Bibtex

@inbook{bae8e91b3e9c4866a2b93cf75a40d279,
title = "Computational Medicinal Chemistry to Target GPCRs",
abstract = "In this chapter, we aim to summarize the most important and most relevant computational medicinal chemistry approaches used in the discovery of GPCR ligands. We introduce the applied computational methods and resources through the most frequent tasks/problems researchers encounter during computational studies targeting GPCRs. The chapter starts from structure preparation and goes through the steps of an imaginary comprehensive computational study tackling the questions like selectivity, functional selectivity and biased signaling. The spread of this chapter does not allow to dive deeply into the technical details of the specific methods, rather we refer the reader to more specific reviews. In the text, we mainly highlight the successful applications of the most wide-spread methods available while pointing out potential drawbacks as well.",
keywords = "Docking, GPCR, Homology model, Ligand similarity, Molecular dynamics, Pharmacophores, QSAR, Virtual screening",
author = "Kiss, {D{\'o}ra Judit} and G{\'a}sp{\'a}r P{\'a}ndy-Szekeres and Keser{\H u}, {Gy{\"o}rgy Mikl{\'o}s}",
note = "Publisher Copyright: {\textcopyright} 2022 Elsevier Inc. All rights reserved",
year = "2022",
doi = "10.1016/B978-0-12-820472-6.00208-5",
language = "English",
volume = "2",
pages = "84--114",
booktitle = "Comprehensive Pharmacology",
publisher = "Elsevier",

}

RIS

TY - CHAP

T1 - Computational Medicinal Chemistry to Target GPCRs

AU - Kiss, Dóra Judit

AU - Pándy-Szekeres, Gáspár

AU - Keserű, György Miklós

N1 - Publisher Copyright: © 2022 Elsevier Inc. All rights reserved

PY - 2022

Y1 - 2022

N2 - In this chapter, we aim to summarize the most important and most relevant computational medicinal chemistry approaches used in the discovery of GPCR ligands. We introduce the applied computational methods and resources through the most frequent tasks/problems researchers encounter during computational studies targeting GPCRs. The chapter starts from structure preparation and goes through the steps of an imaginary comprehensive computational study tackling the questions like selectivity, functional selectivity and biased signaling. The spread of this chapter does not allow to dive deeply into the technical details of the specific methods, rather we refer the reader to more specific reviews. In the text, we mainly highlight the successful applications of the most wide-spread methods available while pointing out potential drawbacks as well.

AB - In this chapter, we aim to summarize the most important and most relevant computational medicinal chemistry approaches used in the discovery of GPCR ligands. We introduce the applied computational methods and resources through the most frequent tasks/problems researchers encounter during computational studies targeting GPCRs. The chapter starts from structure preparation and goes through the steps of an imaginary comprehensive computational study tackling the questions like selectivity, functional selectivity and biased signaling. The spread of this chapter does not allow to dive deeply into the technical details of the specific methods, rather we refer the reader to more specific reviews. In the text, we mainly highlight the successful applications of the most wide-spread methods available while pointing out potential drawbacks as well.

KW - Docking

KW - GPCR

KW - Homology model

KW - Ligand similarity

KW - Molecular dynamics

KW - Pharmacophores

KW - QSAR

KW - Virtual screening

U2 - 10.1016/B978-0-12-820472-6.00208-5

DO - 10.1016/B978-0-12-820472-6.00208-5

M3 - Book chapter

AN - SCOPUS:85151182781

VL - 2

SP - 84

EP - 114

BT - Comprehensive Pharmacology

PB - Elsevier

ER -

ID: 343168147